Computing system with channel estimation mechanism and method of operation thereof

ABSTRACT

A computing system includes: an inter-device interface configured to receive receiver signal for communicating serving content through a communication channel; a communication unit, coupled to the inter-device interface, configured to: calculate a weighting set corresponding to a modular estimation mechanism, and generate a channel estimate based on the weighting set for characterizing the communication channel for recovering the serving content.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 62/050,879 filed Sep. 16, 2014, and the subjectmatter thereof is incorporated herein by reference thereto.

TECHNICAL FIELD

An embodiment described herein relates generally to a computing system,and more particularly to a system with channel estimation mechanism.

BACKGROUND

Modern consumer and industrial electronics, especially devices such ascellular phones, navigations systems, portable digital assistants, andcombination devices, are providing increasing levels of functionality tosupport modern life including mobile communication. Research anddevelopment in the existing technologies can take a myriad of differentdirections.

The increasing demand for information in modern life requires users toaccess information at any time, at increasing data rates. However,telecommunication signals used in mobile communication effectivelyexperience various types of interferences from numerous sources, as wellas computational complexities rising from numerous possible formats forcommunicated information, which affect the quality and speed of theaccessible data.

Thus, a need still remains for a computing system with channelestimation mechanism. In view of the ever-increasing commercialcompetitive pressures, along with growing consumer expectations and thediminishing opportunities for meaningful product differentiation in themarketplace, addressing such issues are becoming increasingly valuable.Additionally, the need to reduce costs, improve efficiencies andperformance, and meet competitive pressures adds an even greater urgencyfor finding answers to these problems.

Solutions to these problems have been long sought but prior developmentshave not taught or suggested any solutions and, thus, solutions to theseproblems have long eluded those skilled in the art.

SUMMARY

An embodiment described herein provides a computing system, including:an inter-device interface configured to receive receiver signal forcommunicating serving content through a communication channel; acommunication unit, coupled to the inter-device interface, configuredto: calculate a weighting set corresponding to a modular estimationmechanism, and generate a channel estimate set based on the weightingset for characterizing the communication channel for recovering theserving content.

An embodiment described herein provides a method of operation of acomputing system including: receiving receiver signal for communicatingserving content through a communication channel; calculating a weightingset corresponding to a modular estimation mechanism; and generating achannel estimate set with a communication unit based on the weightingset for characterizing the communication channel for recovering theserving content.

An embodiment described herein provides a non-transitory computerreadable medium including instructions for operating a computing systemincluding: receiving receiver signal for communicating serving contentthrough a communication channel; calculating a weighting setcorresponding to a modular estimation mechanism; and generating achannel estimate set with a communication unit based on the weightingset for characterizing the communication channel for recovering theserving content.

Certain embodiments have other steps or elements in addition to or inplace of those mentioned above. The steps or elements will becomeapparent to those skilled in the art from a reading of the followingdetailed description when taken with reference to the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a computing system with channel estimation mechanism in anembodiment.

FIG. 2 is an exemplary block diagram of the computing system.

FIG. 3 is a control flow of the computing system.

FIG. 4 is a flow chart of a method of operation of a computing system ina further embodiment.

DETAILED DESCRIPTION

The following embodiments can be used to estimate effects or influencesof communication channel for communicating serving content betweendevices. The communication channel can be estimated using a channelestimate set or an estimate element therein.

The channel estimate set can be generated using a modular estimationmechanism including a reference processing mechanism for smoothingreference portions within receiver signal, a frequency-domain mechanismfor processing the smoothed instances of the reference portions infrequency domain, and a time-domain mechanism for interpolating in timedomain based on result of the frequency-domain mechanism. The channelestimate set can further be generated using the modular estimationmechanism including a combining mechanism and the time-domain mechanism.The combining mechanism can combine the reference processing mechanismand the frequency-domain mechanism into a single process.

The following embodiments are described in sufficient detail to enablethose skilled in the art to make and use the embodiments describedherein. It is to be understood that other embodiments would be evidentbased on the present disclosure, and that system, process, or mechanicalchanges may be made without departing from the scope of an embodiment.

In the following description, numerous specific details are given toprovide a thorough understanding of an embodiment. However, it will beapparent that an embodiment may be practiced without these specificdetails. In order to avoid obscuring an embodiment, some well-knowncircuits, system configurations, and process steps are not disclosed indetail.

The drawings showing embodiments of the system are semi-diagrammatic,and not to scale and, particularly, some of the dimensions are for theclarity of presentation and are shown exaggerated in the drawingfigures. Similarly, although the views in the drawings for ease ofdescription generally show similar orientations, this depiction in thefigures is arbitrary for the most part. Generally, an embodiment can beoperated in any orientation. The embodiments have been numbered firstembodiment, second embodiment, etc. as a matter of descriptiveconvenience and are not intended to have any other significance orprovide limitations for an embodiment.

The term “module” referred to herein can include or be implemented assoftware, hardware, or a combination thereof in an embodiment describedherein in accordance with the context in which the term is used. Forexample, the software can be machine code, firmware, embedded code, andapplication software. The software can also include a function, a callto a function, a code block, or a combination thereof. Also for example,the hardware can be gates, circuitry, processor, computer, integratedcircuit, integrated circuit cores, a pressure sensor, an inertialsensor, a microelectromechanical system (MEMS), passive devices,physical non-transitory memory medium having instructions for performingthe software function, a portion therein, or a combination thereof.

The term “processing” as used herein includes manipulating signal andcorresponding data, such as filtering, detecting, decoding, assemblingdata structures, transferring data structures, manipulating datastructures, and reading and writing data structures. Data structures aredefined to be information arranged as symbols, packets, blocks, files,input data, system generated data, such as calculated or generated data,and program data.

Referring now to FIG. 1, therein is shown a computing system 100 withchannel estimation mechanism in an embodiment. The computing system 100includes a first device 102, such as a mobile device including acellular phone or a notebook computer, connected to a network 104. Thefirst device 102 can further include a wired device, such as a modem ora router. The first device 102 can further include a circuit or a devicewithin a comprehensive device. The first device 102 can include a userequipment (UE).

The network 104 is a system of wired or wireless communication devicesor means that are connected to each other for enabling communicationbetween devices. For example, the network 104 can include a combinationof wires, transmitters, receivers, antennas, towers, stations,repeaters, telephone network, servers, or client devices for a wirelesscellular network. The network 104 can also include a combination ofrouters, cables, computers, servers, and client devices for varioussized area networks. Also for example, the network 104 can include acommunication bus, a wire, a cable, a wireless connection, or acombination thereof between units within a device.

The computing system 100 can include a second device 106 for directly orindirectly linking and communicating with the first device 102. Thenetwork 104 can include or couple to the second device 106. The seconddevice 106 can receive signals from the first device 102, transmitsignals to the first device 102, process signals, or a combinationthereof. The second device 106 can also relay signals between other basestations, components within the network 104, or a combination thereof.

The first device 102 can be connected to the network 104 through thesecond device 106. For example, the second device 106 can be acoordinating device or a controlling device for communication in thecomputing system 100, a base station, an evolved node B (eNodeB), aserver, a router, a modem, or a combination thereof. Also for example,the second device 106 can be a communication device or a processingcomponent included or with a cell tower, a wireless router, an antenna,or a combination thereof being used to communicate with, such as bysending signals to or receiving signals from, the first device 102including a mobile computing device.

The first device 102 can connect to and communicate with other devices,such as other mobile devices, servers, computers, telephones, or acombination thereof. For example, the first device 102 can communicatewith other devices by transmitting signals, receiving signals,processing signals, or a combination thereof and displaying content ofthe signals, audibly recreating sounds according to the content of thesignals, processing according to the content, such as storing anapplication or updating an operating system, or a combination thereof.

The second device 106 can be used to wirelessly exchange signals forcommunication, including voice signals of a telephone call or datarepresenting a webpage and interactions therewith. The second device 106can also transmit reference signals, training signals, error detectionsignals, error correction signals, header information, transmissionformat, protocol information, or a combination thereof.

Based on the communication method, such as code division multiple access(CDMA), orthogonal frequency-division multiple access (OFDMA), ThirdGeneration Partnership Project (3GPP), Long Term Evolution (LTE), orfourth generation (4G) standards, the communication signals can includea header portion, a format portion, an error correction or detectionportion, or a combination thereof imbedded in the communicatedinformation. The header portion, format portion, error correction ordetection portion, or a combination thereof can include a predeterminedbit, pulse, wave, symbol, or a combination thereof. The various portionscan be embedded within the communicated signals at regular timeintervals, frequency, code, or a combination thereof.

The computing system 100 can communicate serving signal 108 forcommunicating serving content 110 between devices. The serving content110 can include information or data intended for communication betweendevices.

For example, the serving content 110 can be information intended forcommunication between the first device 102 and the second device 106. Asa more specific example, the serving content 108 can include informationor data to be executed or implemented at an intended receiving device,communicated through the intended receiving device, or a combinationthereof, such as voice signals, images, instructions, program data,execution steps, or a combination thereof.

The computing system 100 can process the serving content 110 forcommunication to generate the serving signal 108. The computing system100 can use the first device 102, the second device 106, or acombination thereof to process the serving content 110 and generate thecorresponding instance of the serving signal 108.

For example, the computing system 100 can process the serving content110 by encoding the serving content 110, such as according to TurboCoding scheme or Polar Coding scheme. Also for example, the computingsystem 100 can generate and add error detection information, headerinformation, format information, or a combination thereof for theserving content 110 or a derivative thereof. Also for example, thecomputing system 100 can generate one or a sequence of symbolscorresponding to the serving content 110 or a processing derivativethereof according to a modulation scheme or a modulation constellation.

The computing system 100 can process the serving content 110 accordingto a method, a process, a scheme, or a combination thereof predeterminedby the computing system 100, a communication standard or requirement, ora combination thereof. The computing system 100 can further process theserving content 110 based on a characteristic of communicationenvironment, a characteristic of the serving content 110, or acombination thereof.

The computing system 100 can further process the serving content 110 bygrouping, organizing, structuring, or a combination thereof for theserving signal 108. For example, the computing system 100 can generatethe serving signal 108 including one or more instances of a resourceblock 112, a resource element 114, a reference portion 116, or acombination thereof.

The resource block 112 can include a grouping or an organization forinformation for communicating the serving content 110 between devices.The resource block 112 can include a grouping of symbols. The resourceblock 112 can include a size in frequency, time, or a combinationthereof. As a more specific example, the resource block 112 can have asize of 180 kilohertz (kHz) in frequency, 0.5 millisecond (ms) in time,or a combination thereof for LTE communication standard.

The resource element 114 can include a unit or a segment within theresource block 112 for communicating one instance of a unit ofinformation. The resource element 114 can include the unit of resourceallocation. Within one instance of the resource block 112, the symbolscorresponding to the serving content 110 can be mapped to one or moreinstances of the resource element 114 in the two dimensional space oftime and frequency. For example, the resource element 114 can be theunit or the segment designated for communicating one or a limited numberof instances of a bit, a symbol, a code word, a portion therein, or acombination thereof. Continuing with the more specific example, theresource block 112 can include 84 instances of the resource element 114for the LTE standard.

The reference portion 116 can include one or more instances of theresource element 114 designated for communicating known or standardizedinformation. The reference portion 116 can include a reference signalaccording to the communication system 100, the communication standard,or a combination thereof. The reference portion 116 can be fornormalizing signal or for use as pilot information.

The serving signal 108 can be communicated using one or more instancesof a sub-carrier 118, a sub-frame 120, or a combination thereof. Thesub-carrier 118 can include a unit, a division, or a grouping offrequencies within an overall range for communicating information. Eachinstance of the sub-carrier 118 can communicate similar or differentinformation. The sub-frame 120 can include a unit, a division, or a slotin time within an overall range for communicating information. Eachinstance of the sub-frame 120 can communicate similar or differentinformation.

Continuing with the more specific example, the resource block 112 caninclude 12 instances of the sub-carrier 118 within the 180 kHz, witheach instance of the sub-carrier 118 including 15 kHz. The resourceblock 112 can further include 7 instances of the sub-frame 120 for the0.5 ms. The resource block 112 can be for communicating 7 OFDM symbols.

The computing system 100 can utilize a carrier index 122, a frame index124, or a combination thereof. The carrier index 122 can include areference or a name for identifying each instance of the sub-carrier118. The frame index 124 can include a reference or a name foridentifying each instance of the sub-frame 120. The carrier index 122,the frame index 124, or a combination thereof can be for referencing thesub-carrier 118, the sub-frame 120, or a combination thereof within oneinstance of the resource block 112.

The computing system 100 can identify each instance of the resourceelement 114 utilizing a unique value of the carrier index 122, the frameindex 124, or a combination thereof. The computing system 100 caninclude the resource block 112 with the reference portion 116 atdesignated values or instances of the carrier index 122, the frame index124, or a combination thereof according to the computing system 100, thecommunication standard, first device 102, the second device 106, or acombination thereof.

The serving signal 108 can traverse through communication channel 126and be received as receiver signal 128. The communication channel 126can include environments or connections between devices exchangingsignals.

The communication channel 126 can each include be a direct link betweencorresponding devices, such as between the UE and the base station. Thecommunication channel 126 can correspond to signals intended forexchange between corresponding devices, such as between the first device102 and the second device 106.

The communication channel 126 can include repeaters, amplifiers, or acombination thereof there-between for an indirect link. Thecommunication channel 126 can further include a specific instance orparameter of communication detail, such as frequency, time slot, packetdesignation, transmission rate, channel code, or a combination thereofused for transmitting signals between intended devices.

The communication channel 126 can further include physicalcharacteristics unique to geographic locations associated with thecorresponding devices. The communication channel 126 can includestructures or influences, such as fading characteristics of signals orcauses for unique delay or reflection of signals, affecting thetransmission of wireless signals. The communication channel 126 canfurther include signals from other sources interfering with thecommunication of the serving signal 108. The communication channel 126can distort or alter the signals traversing therein.

The receiver signal 128 can include information perceived or received ata receiving device. The receiver signal 128 can include informationdetected or identified at the receiving device. The receiver signal 128can correspond to the serving signal 108. The receiver signal 128 can bethe information corresponding to the serving signal 108 received at theintended device. The receiver signal 128 can be represented as ‘y’.

The receiver signal 128 can include components or portions correspondingto the serving signal 108. For example, the receiver signal 128 caninclude components or portions corresponding to the resource block 112,the resource element 114, the reference portion 116, or a combinationthereof. Also for example, the receiver signal 128 can includecomponents or portions corresponding to the sub-carrier 118, thesub-frame 120, or a combination thereof. The computing system 100 canutilize the carrier index 122, the frame index 124, or a combinationthereof to process the receiver signal 128.

The receiver signal 128 can include a noise component. The noisecomponent can include errors, influences, changes, or a combinationthereof affecting accuracy of the data. The noise component can includeadditive Gaussian white noise (AGWN) or variations based on Rayleighdistribution. The noise component can further include inaccuracies,hardware limitations, or a combination thereof from the transmittingdevice or the second device 106, the receiving device or the firstdevice 102, the communication channel 126, the network 104, or acombination thereof.

The noise component can be represented as ‘z’. The noise component caninclude a noise measure 130. The noise measure 130 can include acharacteristic or a trait of the noise component. The noise measure 130can include a statistical description or representation of the noisecomponent. For example, the noise measure 130 can include a covarianceor a standard deviation for the noise component of the receiver signal128.

The noise measure 130 can be represented as ‘σ²I’ or ‘σ²’. The term ‘I’can represent an identity matrix with a size or a dimensioncorresponding to the receiver signal 128 or a portion therein.

The receiver signal 128 can further include a channel output portion132. The channel output portion 132 can be the information correspondingdirectly to the reference portion 116 of the serving signal 108. Thechannel output portion 132 can include a segment or a component of thereceiver signal 128 directly associated with the reference portion 116of the serving signal 108. The channel output portion 132 can includethe segment or the component of the receiver signal 128 corresponding tothe reference portion 116 and excluding the noise component, excludingan interference component, or a combination thereof independent of theserving signal 108.

The channel output portion 132 can further include a result of thereference portion 116 of the serving signal 108 after being affected orinfluenced by the communication channel 126. The channel output portion132 can be represented as ‘p’. Similarly, the receiver signal 128 or aportion or the segment of the receiver signal 128 corresponding to thereference portion 116 can be represented using channel output portion132 and the noise component as:

y=p+z.  Equation (1).

The channel output portion 132 can include the serving signal 108 and achannel estimate 134 including one or more instance of estimate element136. The estimate element 136 is a description or a representation ofthe influence or the alteration caused by the communication channel 126for a specific portion of the serving signal 108.

The estimate element 136 can correspond to an instance of thesub-carrier 118, an instance of the sub-frame 120, or a combinationthereof. The estimate element 136 can be referenced by the carrier index122, the frame index 124, or a combination thereof. For example, theestimate element 136 can be represented as ‘ĥ_(k,l)’ according to thecarrier index 122 and the frame index 124. Similarly, the receiversignal 128 can be further represented as:

y=hx+z.  Equation (2).

The channel estimate 134 is an overall description or an overallrepresentation of the influence of the alteration caused by thecommunication channel 126 for the serving signal 108 overall. Thechannel estimate 134 can include one or more instances of the estimateelement 136 corresponding to each of the portions in the serving signal108.

For example, the estimate element 136 can include the description or therepresentation corresponding to the resource element 114 or thereference portion 116. The channel estimate 134 can include thedescription or the representation corresponding to one or more instancesof the resource block 112 including one or more instances of theresource element 114, the reference portion 116, or a combinationthereof.

For illustrative purposes, the computing system 100 is described as thefirst device 102 being a UE receiving the receiver signal 128corresponding to the serving signal 108 transmitted by the second device106 intended for the first device 102. However, it is understood thatthe first device 102 can also transmit information and the second device106 can also receive signals. It is also understood that the firstdevice 102 can include a planning device, a base station, or acombination thereof. It is also understood that the second device 106can include a UE.

The computing system 100 can generate the channel estimate 134, theestimate element 136, or a combination thereof based on the receiversignal 128. The computing system 100 can use the channel estimate 134,the estimate element 136, or a combination thereof to further processthe receiver signal 128 and recover the serving content 110 originallyintended for communication. The computing system 100 can further use thechannel estimate 134, the estimate element 136, or a combination thereoffor feedback information, for controlling or modifying controlparameters or processing mechanisms, or a combination thereof.

The computing system 100 can generate the channel estimate 134 using amodular estimation mechanism 138 or a naïve-comprehensive mechanism 140.The computing system 100 can use the modular estimation mechanism 138instead of or in place of the naïve-comprehensive mechanism 140.

The naïve-comprehensive mechanism 140 is a method or a process utilizedfor comprehensively generating the channel estimate 134. Thenaïve-comprehensive mechanism 140 can implement the method or theprocess as one grouping for process implementation count 142representing groupings or organization of functions or results requiredfor generating the channel estimate. The naïve-comprehensive mechanism140 can be for implementing:

ĥ _(k,l) =R _(h) _(k,l) _(P)(R _(pp)+σ² I)⁻¹ y.  Equation (3).

The modular estimation mechanism 138 is a method or a process utilizedfor generating the channel estimate 134 using distinctive segments orgroupings within the method or the process. The modular estimationmechanism 138 can assume that channel correlation can be represented bythe product of time and frequency dependent terms. The modularestimation mechanism 138 can correspond to the process implementationcount 142 of two or more. For example, the modular estimation mechanism138 can be for implementing Equation (3) using two, three, or moreinstances of segments or groups performing separate functions, methods,processes, or a combination thereof.

The modular estimation mechanism 138 can include implementation formulti-correlation result 144, auto-correlation result 146, or acombination thereof. The multi-correlation result 144 can represent arelationship between actual effect from the communication channel 126and the received information. The multi-correlation result 144 can berepresented as ‘R_(h) _(k,l) _(p)’.

For example, the multi-correlation result 144 can represent therelationship between the actual effect or distortion caused by thecommunication channel 126 and the channel output portion 132. Also forexample, the multi-correlation result 144 can be based on mathematicalcorrelation between the actual effect or distortion caused by thecommunication channel 126 for the resource element 114 for a specificinstance of the carrier index 122 and the frame index 124, representedas ‘h_(k,l)’, and the channel output portion 132, represented as ‘p’.

The auto-correlation result 146 can represent a relationship or apattern within the received information relevant to estimating thecommunication channel 126. The auto-correlation result 146 can be therelationship or the pattern within the channel output portion 132. Theauto-correlation result 146 can be based on mathematicalauto-correlation for the channel output portion 132. Theauto-correlation result 146 can be represented as ‘R_(pp)’.

The modular estimation mechanism 138 can be for implementingminimum-mean-square-error (MMSE) estimation scheme or linear MMSE(LMMSE) estimation scheme. The modular estimation mechanism 138 canimplement MMSE or LMMSE using second order statistics of thecommunication channel 126. The modular estimation mechanism 138 canutilize the second order statistics and minimize the mean-square-error(MSE) within estimations for the effects or changes caused by thecommunication channel 126.

The modular estimation mechanism 138 can further generate the channelestimate 134 without utilizing residual error 148. The residual error148 is an error in estimating the effects or changes caused by thecommunication channel 126. The residual error 148 can correspond to oneor more instances of the resource element 114, as referenced by thecarrier index 122 and the frame index 124. The residual error 148 can berepresented as ‘e_(k,l)’.

Outside of the modular estimation mechanism 138, the residual error 148can be utilized. The residual error 148 can be based on:

$\begin{matrix}{\sigma_{e}^{2} = {{\frac{1}{N}{\sum\limits_{k = 0}^{N - 1}\; {E\left\lbrack {e_{k,l_{1}}e_{k,l_{1}}^{*}} \right\rbrack}}}..}} & {{Equation}\mspace{14mu} (4)}\end{matrix}$

The computing system 100 and the modular estimation mechanism 138 cangenerate the channel estimate 134 without estimating and withoututilizing the residual error 148. The modular estimation mechanism 138can utilize the noise measure 130 without the further processingrequired for the residual error 148.

The modular estimation mechanism 138 can include processing informationin a frequency domain 150, a time domain 152, or a combination thereof.The two-dimensional aspect of the modular estimation mechanism 138 cancorrespond to the frequency domain 150 and the time domain 152 eachcorresponding to one of the two dimensions.

The frequency domain 150 can include a particular area or system ofrepresentation for information associated with frequency. For example,the computing system 100 can represent a signal by the frequencycomponents therein, a magnitude or an amount of effect thereof, or acombination thereof in the frequency domain 150.

The time domain 152 can include a particular area or system ofrepresentation for information associated with time. For example, thecomputing system 100 can represent a signal by magnitudes and timing, aspecific time, a relative comparison, or a combination thereofassociated with detection of the magnitude.

The computing system 100 can use the modular estimation mechanism 138based on a correlation mechanism 154. The correlation mechanism 154 is amethod or a process for calculating a relationship between differentsets of data or for calculating a pattern or a relationship within a setof data. The correlation mechanism 154 can be for calculating themathematical correlation or the mathematical auto-correlation. Thecorrelation mechanism 154 can include a frequency-correlation function156, a time-correlation function 158, or a combination thereof.

The frequency-correlation function 156 is a method or a process forcalculating a relationship between different sets of data in thefrequency domain 150 or for calculating a pattern or a relationshipwithin a set of data in the frequency domain 150. Thefrequency-correlation function 156 can analyze or process the dataexisting in or corresponding to the frequency domain 150, analyze orprocess in the frequency domain 150, or a combination thereof. Thefrequency-correlation function 156 can be represented as ‘r_(f) (•)’.

The time-correlation function 158 is a method or a process forcalculating a relationship between different sets of data in the timedomain 152 or for calculating a pattern or a relationship within a setof data in the time domain 152. The time-correlation function 158 cananalyze or process the data existing in or corresponding to the timedomain 152, analyze or process in the time domain 152, or a combinationthereof. The time-correlation function 158 can be represented as ‘r_(t)(•)’.

The computing system 100 can utilize the modular estimation mechanism138 based on the correlation mechanism 154 including thefrequency-correlation function 156, the time-correlation function 158,or a combination thereof. For example, the computing system 100 canimplement Equation (3) using the frequency-correlation function 156, thetime-correlation function 158, or a combination thereof.

As a more specific example, the computing system 100 can assumeWide-Sense Stationary Uncorrelated Scattering (WSSUS) channel model forgenerating the channel estimate 134. The correlation between the effector the alteration caused by the communication channel 126 for twodifferent instances of the resource element 114 can be represented as:

R _(h) _(i,j) _(h) _(k,l) =E[h _(i,j) k* _(k,l) ]=r _(f)(i−k)r_(t)(j−l).  Equation (5).

The correlation across the effects or the changes of the communicationchannel 126 for the two different instances of the resource element 114can be represented as ‘R_(h) _(i,j) _(h) _(k,l) ’, and the two differentinstances effects or the changes can be represented as ‘h_(i,j)’ and‘h_(k,l)’. The terms ‘i’ and ‘k’ and be two different values orinstances of the carrier index 122 and the terms ‘j’ and ‘l’ can be twodifferent values or instances of the frame index 124.

The computing system 100 can use the modular estimation mechanism 138 tocalculate a weighting set 160 in generating the channel estimate 134.The weighting set 160 is a group of parameters for implementing eachdistinct process grouping or segmentations corresponding to the channeloutput portion 132.

For example the weighting set 160 can include two or more distinctparameters or sets thereof for the modular estimation mechanism 138. Theweighting set 160 can include a group of values or value sets, such as ascalar, a calculation or processing result, a matrix or an array, or acombination thereof each corresponding to one of the distinct processgrouping or segmentations within the modular estimation mechanism 138.

The computing system 100 can implement the various mechanisms describedabove in various ways. For example, the computing system 100 canimplement the modular estimation mechanism 138, the correlationmechanism 154, or a combination thereof using hardware, software,firmware, or a combination thereof. As a more specific example, thevarious mechanisms can be implemented using circuits, active or passive,gates, arrays, feedback loops, feed-forward loops, hardware connections,functions or function calls, instructions, equations, datamanipulations, structures, addresses, or a combination thereof.

For illustrative purposes, the computing system 100 is described as thebase station communicating information to the mobile device, such as thebase station transmitting and the mobile device receiving theinformation. However, it is understood that the mobile device cancommunicate directly to each other or to the base station.

Referring now to FIG. 2, therein is shown an exemplary block diagram ofthe computing system 100. The computing system 100 can include the firstdevice 102, the network 104, and the second device 106. The first device102 can send information in a first device transmission 208 over thenetwork 104 to the second device 106. The second device 106 can sendinformation in a second device transmission 210 over the network 104 tothe first device 102.

For illustrative purposes, the computing system 100 is shown with thefirst device 102 as a client device, although it is understood that thecomputing system 100 can have the first device 102 as a different typeof device. For example, the first device 102 can be a server having adisplay interface.

Also for illustrative purposes, the computing system 100 is shown withthe second device 106 as a server, although it is understood that thecomputing system 100 can have the second device 106 as a different typeof device. For example, the second device 106 can be a client device.

For brevity of description in this embodiment of the present invention,the first device 102 will be described as a client device and the seconddevice 106 will be described as a server device. The embodiment of thepresent invention is not limited to this selection for the type ofdevices. The selection is an example of an embodiment of the presentinvention.

The first device 102 can include a first control unit 212, a firststorage unit 214, a first communication unit 216, and a first userinterface 218. The first control unit 212 can include a first controlinterface 222. The first control unit 212 can execute a first software226 to provide the intelligence of the computing system 100.

The first control unit 212 can be implemented in a number of differentmanners. For example, the first control unit 212 can be a processor, anapplication specific integrated circuit (ASIC) an embedded processor, amicroprocessor, a hardware control logic, a hardware finite statemachine (FSM), a digital signal processor (DSP), or a combinationthereof. The first control interface 222 can be used for communicationbetween the first control unit 212 and other functional units in thefirst device 102. The first control interface 222 can also be used forcommunication that is external to the first device 102.

The first control interface 222 can receive information from the otherfunctional units or from external sources, or can transmit informationto the other functional units or to external destinations. The externalsources and the external destinations refer to sources and destinationsexternal to the first device 102.

The first control interface 222 can be implemented in different ways andcan include different implementations depending on which functionalunits or external units are being interfaced with the first controlinterface 222. For example, the first control interface 222 can beimplemented with a pressure sensor, an inertial sensor, amicroelectromechanical system (MEMS), optical circuitry, waveguides,wireless circuitry, wireline circuitry, or a combination thereof.

The first storage unit 214 can store the first software 226. The firststorage unit 214 can also store the relevant information, such as datarepresenting incoming images, data representing previously presentedimage, sound files, or a combination thereof.

The first storage unit 214 can be a volatile memory, a nonvolatilememory, an internal memory, an external memory, or a combinationthereof. For example, the first storage unit 214 can be a nonvolatilestorage such as non-volatile random access memory (NVRAM), Flash memory,disk storage, or a volatile storage such as static random access memory(SRAM).

The first storage unit 214 can include a first storage interface 224.The first storage interface 224 can be used for communication betweenthe first storage unit 214 and other functional units in the firstdevice 102. The first storage interface 224 can also be used forcommunication that is external to the first device 102.

The first storage interface 224 can receive information from the otherfunctional units or from external sources, or can transmit informationto the other functional units or to external destinations. The externalsources and the external destinations refer to sources and destinationsexternal to the first device 102.

The first storage interface 224 can include different implementationsdepending on which functional units or external units are beinginterfaced with the first storage unit 214. The first storage interface224 can be implemented with technologies and techniques similar to theimplementation of the first control interface 222.

The first communication unit 216 can enable external communication toand from the first device 102. For example, the first communication unit216 can permit the first device 102 to communicate with the seconddevice 106, a different device, an attachment, such as a peripheraldevice or a desktop computer, the network 104, or a combination thereof.

The first communication unit 216 can also function as a communicationhub allowing the first device 102 to function as part of the network 104and not limited to be an end point or terminal unit to the network 104.The first communication unit 216 can include active and passivecomponents, such as microelectronics or an antenna, for interaction withthe network 104.

The first communication unit 216 can include a baseband device orcomponent, a modem, a digital signal processor, or a combination thereoffor transmitting, formatting, receiving, detecting, decoding, furtherprocessing, or a combination thereof for communication signals. Thefirst communication unit 216 can include one or more portions forprocessing the voltages, the currents, the digital information, or acombination thereof, such as an analog-to-digital converter, adigital-to-analog converter, a filter, an amplifier, a processor-typecircuitry, or a combination thereof. The first communication unit 216can further include one or more portions for storing information, suchas cache or RAM memory, registers, or a combination thereof.

The first communication unit 216 can be coupled with a firstinter-device interface 217. The first inter-device interface 217 can bea device or a portion of a device for physically communicating signalswith a separate device. The first inter-device interface 217 cancommunicate by transmitting or receiving signals to or from anotherdevice. The first inter-device interface 217 can include one or moreantennas for wireless signals, a physical connection andreceiver-transmitter for wired signals, or a combination thereof. Thefirst inter-device interface 217 can include an omnidirectional antenna,a wire, an antenna chip, a ceramic antenna, or a combination thereof.The first inter-device interface 217 can further include a port, a wire,a repeater, a connector, a filter, a sensor, or a combination thereof.

The first inter-device interface 217 can detect or respond to a power inelectromagnetic waves and provide the detected result to the firstcommunication unit 216 to receive a signal, including the second devicetransmission 210. The first inter-device interface 217 can provide apath or respond to currents or voltages provided by the firstcommunication unit 216 to transmit a signal, including the first devicetransmission 208.

The first communication unit 216 can include a first communicationinterface 228. The first communication interface 228 can be used forcommunication between the first communication unit 216 and otherfunctional units in the first device 102. The first communicationinterface 228 can receive information from the other functional units orcan transmit information to the other functional units.

The first communication interface 228 can include differentimplementations depending on which functional units are being interfacedwith the first communication unit 216. The first communication interface228 can be implemented with technologies and techniques similar to theimplementation of the first control interface 222.

The first user interface 218 allows a user (not shown) to interface andinteract with the first device 102. The first user interface 218 caninclude an input device and an output device. Examples of the inputdevice of the first user interface 218 can include a keypad, a touchpad,soft-keys, a keyboard, a microphone, an infrared sensor for receivingremote signals, or any combination thereof to provide data andcommunication inputs.

The first user interface 218 can include a first display interface 230.The first display interface 230 can include an output device. The firstdisplay interface 230 can include a display, a projector, a videoscreen, a speaker, or any combination thereof.

The first control unit 212 can operate the first user interface 218 todisplay information generated by the computing system 100. The firstcontrol unit 212 can also execute the first software 226 for the otherfunctions of the computing system 100. The first control unit 212 canfurther execute the first software 226 for interaction with the network104 via the first communication unit 216.

The second device 106 can be optimized for implementing an embodiment ofthe present invention in a multiple device embodiment with the firstdevice 102. The second device 106 can provide the additional or higherperformance processing power compared to the first device 102. Thesecond device 106 can include a second control unit 234, a secondcommunication unit 236, a second user interface 238, and a secondstorage unit 246.

The second user interface 238 allows a user (not shown) to interface andinteract with the second device 106. The second user interface 238 caninclude an input device and an output device. Examples of the inputdevice of the second user interface 238 can include a keypad, atouchpad, soft-keys, a keyboard, a microphone, or any combinationthereof to provide data and communication inputs. Examples of the outputdevice of the second user interface 238 can include a second displayinterface 240. The second display interface 240 can include a display, aprojector, a video screen, a speaker, or any combination thereof.

The second control unit 234 can execute a second software 242 to providethe intelligence of the second device 106 of the computing system 100.The second software 242 can operate in conjunction with the firstsoftware 226. The second control unit 234 can provide additionalperformance compared to the first control unit 212.

The second control unit 234 can operate the second user interface 238 todisplay information. The second control unit 234 can also execute thesecond software 242 for the other functions of the computing system 100,including operating the second communication unit 236 to communicatewith the first device 102 over the network 104.

The second control unit 234 can be implemented in a number of differentmanners. For example, the second control unit 234 can be a processor, anembedded processor, a microprocessor, hardware control logic, a hardwarefinite state machine (FSM), a digital signal processor (DSP), or acombination thereof.

The second control unit 234 can include a second control interface 244.The second control interface 244 can be used for communication betweenthe second control unit 234 and other functional units in the seconddevice 106. The second control interface 244 can also be used forcommunication that is external to the second device 106.

The second control interface 244 can receive information from the otherfunctional units or from external sources, or can transmit informationto the other functional units or to external destinations. The externalsources and the external destinations refer to sources and destinationsexternal to the second device 106.

The second control interface 244 can be implemented in different waysand can include different implementations depending on which functionalunits or external units are being interfaced with the second controlinterface 244. For example, the second control interface 244 can beimplemented with a pressure sensor, an inertial sensor, amicroelectromechanical system (MEMS), optical circuitry, waveguides,wireless circuitry, wireline circuitry, or a combination thereof.

A second storage unit 246 can store the second software 242. The secondstorage unit 246 can also store the information such as datarepresenting incoming images, data representing previously presentedimage, sound files, or a combination thereof. The second storage unit246 can be sized to provide the additional storage capacity tosupplement the first storage unit 214.

For illustrative purposes, the second storage unit 246 is shown as asingle element, although it is understood that the second storage unit246 can be a distribution of storage elements. Also for illustrativepurposes, the computing system 100 is shown with the second storage unit246 as a single hierarchy storage system, although it is understood thatthe computing system 100 can have the second storage unit 246 in adifferent configuration. For example, the second storage unit 246 can beformed with different storage technologies forming a memory hierarchalsystem including different levels of caching, main memory, rotatingmedia, or off-line storage.

The second storage unit 246 can be a volatile memory, a nonvolatilememory, an internal memory, an external memory, or a combinationthereof. For example, the second storage unit 246 can be a nonvolatilestorage such as non-volatile random access memory (NVRAM), Flash memory,disk storage, or a volatile storage such as static random access memory(SRAM).

The second storage unit 246 can include a second storage interface 248.The second storage interface 248 can be used for communication betweenthe second storage unit 246 and other functional units in the seconddevice 106. The second storage interface 248 can also be used forcommunication that is external to the second device 106.

The second storage interface 248 can receive information from the otherfunctional units or from external sources, or can transmit informationto the other functional units or to external destinations. The externalsources and the external destinations refer to sources and destinationsexternal to the second device 106.

The second storage interface 248 can include different implementationsdepending on which functional units or external units are beinginterfaced with the second storage unit 246. The second storageinterface 248 can be implemented with technologies and techniquessimilar to the implementation of the second control interface 244.

The second communication unit 236 can enable external communication toand from the second device 106. For example, the second communicationunit 236 can permit the second device 106 to communicate with the firstdevice 102 over the network 104.

The second communication unit 236 can also function as a communicationhub allowing the second device 106 to function as part of the network104 and not limited to be an end point or terminal unit to the network104. The second communication unit 236 can include active and passivecomponents, such as microelectronics or resistors, for interaction withthe network 104.

The second communication unit 236 can include a baseband device orcomponent, a modem, a digital signal processor, or a combination thereoffor transmitting, formatting, receiving, detecting, decoding, furtherprocessing, or a combination thereof for communication signals. Thesecond communication unit 236 can include one or more portions forprocessing the voltages, the currents, the digital information, or acombination thereof, such as an analog-to-digital converter, adigital-to-analog converter, a filter, an amplifier, a processor-typecircuitry, or a combination thereof. The second communication unit 236can further include one or more portions for storing information, suchas cache or RAM memory, registers, or a combination thereof.

The second communication unit 236 can be coupled with a secondinter-device interface 237. The second inter-device interface 237 can bea device or a portion of a device for physically communicating signalswith a separate device. The second inter-device interface 237 cancommunicate by transmitting or receiving signals to or from anotherdevice. The second inter-device interface 237 can include one or moreantennas for wireless signals, a physical connection andreceiver-transmitter for wired signals, or a combination thereof. Thesecond inter-device interface 237 can include an omnidirectionalantenna, a wire, an antenna chip, a ceramic antenna, or a combinationthereof. The second inter-device interface 237 can further include aport, a wire, a repeater, a connector, a filter, a sensor, or acombination thereof.

The second inter-device interface 237 can detect or respond to a powerin electromagnetic waves and provide the detected result to the secondcommunication unit 236 to receive a signal, including the first devicetransmission 208. The second inter-device interface 237 can provide apath or respond to currents or voltages provided by the secondcommunication unit 236 to transmit a signal, including the second devicetransmission 210.

The second communication unit 236 can include a second communicationinterface 250. The second communication interface 250 can be used forcommunication between the second communication unit 236 and otherfunctional units in the second device 106. The second communicationinterface 250 can receive information from the other functional units orcan transmit information to the other functional units.

The second communication interface 250 can include differentimplementations depending on which functional units are being interfacedwith the second communication unit 236. The second communicationinterface 250 can be implemented with technologies and techniquessimilar to the implementation of the second control interface 244.

The first communication unit 216 can couple with the network 104 to sendinformation to the second device 106 in the first device transmission208. The second device 106 can receive information in the secondcommunication unit 236 from the first device transmission 208 of thenetwork 104.

The second communication unit 236 can couple with the network 104 tosend information to the first device 102 in the second devicetransmission 210. The first device 102 can receive information in thefirst communication unit 216 from the second device transmission 210 ofthe network 104. The computing system 100 can be executed by the firstcontrol unit 212, the second control unit 234, or a combination thereof.For illustrative purposes, the second device 106 is shown with thepartition having the second user interface 238, the second storage unit246, the second control unit 234, and the second communication unit 236,although it is understood that the second device 106 can have adifferent partition. For example, the second software 242 can bepartitioned differently such that some or all of its function can be inthe second control unit 234 and the second communication unit 236. Also,the second device 106 can include other functional units not shown inFIG. 2 for clarity.

The functional units in the first device 102 can work individually andindependently of the other functional units. The first device 102 canwork individually and independently from the second device 106 and thenetwork 104.

The functional units in the second device 106 can work individually andindependently of the other functional units. The second device 106 canwork individually and independently from the first device 102 and thenetwork 104.

The functional units described above can be implemented in hardware. Forexample, one or more of the functional units can be implemented usingthe a gate, circuitry, a processor, a computer, integrated circuit,integrated circuit cores, a pressure sensor, an inertial sensor, amicroelectromechanical system (MEMS), a passive device, a physicalnon-transitory memory medium having instructions for performing thesoftware function, a portion therein, or a combination thereof.

For illustrative purposes, the computing system 100 is described byoperation of the first device 102 and the second device 106. It isunderstood that the first device 102 and the second device 106 canoperate any of the modules and functions of the computing system 100.

Referring now to FIG. 3, therein is shown a control flow of thecomputing system 100. The computing system 100 can include a receivermodule 302, a channel estimation module 304, a message processing module306, or a combination thereof. The receiver module 302 can be coupledwith the channel estimation module 304, which can be further coupledwith the message processing module 306.

The modules can be coupled to each other in a variety of ways. Forexample, modules can be coupled by having the input of one moduleconnected to the output of another, such as by using wired or wirelessconnections, the network 104 of FIG. 1, instructional steps, processsequence, or a combination thereof. Also for example, the modules can becoupled either directly with no intervening structure other thanconnection means between the directly coupled modules, or indirectlywith modules or devices other than the connection means between theindirectly coupled modules.

As a more specific example, one or more inputs or outputs of thereceiver module 302 can be connected to one or more inputs or outputs ofthe channel estimation module 304 using conductors or the communicationchannel without intervening modules or devices there-between for directcoupling. Also for example, the mechanism receiver module 302 can becoupled to the channel estimation module 304 indirectly using a wirelesschannel with a repeater, a switch, a routing device, or a combinationthereof. The receiver module 302, the channel estimation module 304, themessage processing module 306, or a combination thereof can be coupledin similar ways as described above.

The computing system 100 can communicate information between devices,such as by sending, transmitting, receiving, coding, decoding, or acombination thereof. The receiving device can further communicate withthe user by displaying images, recreating sounds, exchanging processsteps or instructions, or a combination thereof according to theinformation communicate to the device.

The receiver module 302 is configured to communicate the serving content110 of FIG. 1. The receiver module 302 can communicate the servingcontent 110 by receiving the receiver signal 128 of FIG. 1 correspondingto or including the serving signal 108 of FIG. 1 for communicating theserving content 110 through the communication channel 126 of FIG. 1.

The receiver module 302 can receive the receiver signal 128 as theserving signal 108 having traversed the communication channel 126. Thereceiver module 302 can receive the receiver signal 128 as the servingsignal 108 modified, altered, or changed due to the effect, influence,change, or alteration caused by the communication channel 126.

For example, the receiver module 302 can receive the receiver signal 128including one or more portions or segments corresponding to the resourceblock 112 of FIG. 1, the resource element 114 of FIG. 1, the referenceportion 116 of FIG. 1, or a combination thereof. Also for example, thereceiver module 302 can receive the receiver signal 128 corresponding toone or more instances of the sub-carrier 118 of FIG. 1, the sub-frame120 of FIG. 1, or a combination thereof. The receiver module 302 canreceive the receiver signal 128 corresponding to the carrier index 122of FIG. 1, the frame index 124 of FIG. 1, or a combination thereof.

As a more specific example, the receiver module 302 can receive thereceiver signal 128 at the first device 102 of FIG. 1, corresponding tothe serving signal 108 transmitted by the second device 106 of FIG. 1.Also as a more specific example, the receiver module 302 can receive thereceiver signal 128 corresponding to multiple-input multiple-output(MIMO) communication scheme or single-input single-output (SISO)communication scheme.

The receiver module 302 can receive the receiver signal 128 by recordingelectrical power, voltage, current, or a combination thereof. Forexample, the receiver module 302 can receive the receiver signal 128 byrecording energy levels or changes therein for the first inter-deviceinterface 217 of FIG. 2, the second inter-device interface 237 of FIG.2, the first communication interface 228 of FIG. 2, the secondcommunication interface 250 of FIG. 2, the first control interface 222of FIG. 2, the second control interface 244 of FIG. 2, or a combinationthereof.

Also for example, the receiver module 302 can receive the receiversignal 128 by recording energy levels or changes received through awireless antenna, a wire or a conductor, an instruction or a step fortransferring data between devices, processes, instructions, betweenportions therein, or a combination thereof. Also for example, thereceiver module 302 can record the receiver signal 128 by storing theenergy levels or changes therein, according to a time, a sequence, or acombination thereof in the first communication unit 216 of FIG. 2, thesecond communication unit 236 of FIG. 2, the first storage unit 214 ofFIG. 2, the second storage unit 246 of FIG. 2, or a combination thereof.

The receiver module 302 can process the receiver signal 128 to determineaspects thereof. For example, the receiver module 302 can determine oridentify a sample size, a sample index, the resource block 112, thesub-carrier 118, the sub-frame 120, the resource element 114, thereference portion 116, the channel output portion 132 of FIG. 1, thenoise component or the noise measure 130 of FIG. 1, or a combinationthereof. The receiver module 302 can determine the aspects of thereceiver signal 128 based on a method or a process predetermined by thecomputing system 100 or a standard for controlling a sampling rate, ablock size, a symbol size, or a combination thereof.

As a more specific example, the receiver module 302 can utilize timinginformation or control parameters known or communicated to the receivingdevice to determine the aspects or format for the receiver signal 128.Also as a more specific example, the receiver module 302 can utilizespecific transmitter or receiver antenna or the information communicatedthrough the specific antenna, transmission frequencies, transmissiontiming or slots, known formats or arrangements, or a combination thereofto determine the aspects or format for the receiver signal 128.

The receiver module 302 can further use a dedicated device, circuitry,process, or a combination thereof to determine the aspects of thereceiver signal 128 including the noise component, the noise measure130, or a combination thereof. The receiver module 302 can also useknown parts or aspects of the receiver signal 128 to further identifyappropriate instance of the values for other aspects as predeterminedand stored by the computing system 100. The receiver module 302 canfurther determine the noise measure 130 using a statistical analysisbased on the noise component, based on values predetermined by thecomputing system 100, or a combination thereof.

The receiver module 302 can determine the aspects of the receiver signal128 using the first communication unit 216, the second communicationunit 236, the first control unit 212 of FIG. 2, the second control unit234 of FIG. 2, or a combination thereof. The receiver module 302 canstore the aspects of the receiver signal 128 in the first communicationunit 216, the second communication unit 236, the first storage unit 214,the second storage unit 246, or a combination thereof.

After receiving the receiver signal 128 and determining the aspectsthereof, the control flow can pass to the channel estimation module 304.The control flow can pass through a variety of ways. For example,control flow can pass by having processing results of one module passedto another module, such as by passing the receiver signal 128, thedetermined aspects thereof, or a combination thereof from the receivermodule 302 to the channel estimation module 304, by storing theprocessing results at a location known and accessible to the othermodule, such as by storing the receiver signal 128, the determinedaspects thereof, or a combination thereof at a storage location knownand accessible to the channel estimation module 304, by notifying theother module, such as by using a flag, an interrupt, a status signal, ora combination for the channel estimation module 304, or a combination ofprocesses thereof.

The channel estimation module 304 is configured to characterize thecommunication channel 126. The channel estimation module 304 cancharacterize by generating the channel estimate 134 of FIG. 1. Thechannel estimation module 304 can generate the channel estimate 134corresponding to one or more instances of the resource block 112, theresource element 114, or a combination thereof in the receiver signal128, the serving signal 108, or a combination thereof.

The channel estimation module 304 can use the reference portion 116 ofthe serving signal 108, a portion in the receiver signal 128corresponding thereto, or a combination thereof to generate the channelestimate 134. The channel estimation module 304 can further process thereceiver signal 128 with the frequency domain 150 of FIG. 1, the timedomain 152 of FIG. 1, or a combination thereof.

For example, the channel estimation module 304 can compare the receivedinstances of the receiver signal 128 or segments therein to thepredetermined or known parameters for the reference portion 116. Alsofor example, the channel estimation module 304 can further calculate thechanges in magnitude, frequency, phase, or a combination thereof in thereference portion 116 of the serving signal 108 to the receiver signal128.

The channel estimation module 304 can use the modular estimationmechanism 138 of FIG. 1 to generate the channel estimate 134 or one ormore instances of the estimate element 136 of FIG. 1 therein. Thechannel estimation module 304 can generate the channel estimate 134based on the modular estimation mechanism 138 instead of or forreplacing the naïve-comprehensive mechanism 140 of FIG. 1. The channelestimation module 304 can use the modular estimation mechanism 138including a reference processing mechanism 312, a frequency-domainmechanism 314, a time-domain mechanism 316, a combining mechanism 318,or a combination thereof.

The reference processing mechanism 312 is a method or a process formanipulating the reference portion 116. The reference processingmechanism 312 can process one or more instances of the reference portion116 in the receiver signal 128 or a portion therein corresponding to thereference portion 116. The reference processing mechanism 312 caninclude specific instance of the carrier index 122, the sub-frame index124, or a combination thereof predetermined for identifying thereference portion 116 or a portion within the receiver signal 128corresponding thereto.

The frequency-domain mechanism 314 is a method or a process analyzingthe effect or characteristics of the communication channel 126 based oninformation, operation, or a combination thereof in the frequency domain150. The frequency-domain mechanism 314 can include frequency-domainprocessing for OFDM symbols with the reference portion 116. Thefrequency-domain mechanism 314 can utilize the processing result fromimplementing the reference processing mechanism 312. Thefrequency-domain mechanism 314 can include correlation calculation,interpolation, or a combination thereof. The frequency-domain mechanism314 can include the frequency-correlation function 156 of FIG. 1.

The time-domain mechanism 316 is a method or a process analyzing theeffect or characteristics of the communication channel 126 based oninformation, operation, or a combination thereof in the time domain 152.The time-domain mechanism 316 can utilize the processing result fromimplementing the reference processing mechanism 312, thefrequency-domain mechanism 314, or a combination thereof. Thetime-domain mechanism 316 can include correlation calculation,interpolation, or a combination thereof. The time-domain mechanism 316can include the time-correlation function 158 of FIG. 1.

The combining mechanism 318 is a method or a process analyzing theeffect or characteristics of the communication channel 126 based oninformation, operation, or a combination thereof for the referenceportion 116 in the frequency domain 150. The combining mechanism 318 caninclude the reference processing mechanism 312 and the frequency-domainmechanism 314 combined into one grouping or the process implementationcount 142 of FIG. 1 of one.

The channel estimation module 304 can further calculate and utilize theweighting set 160 of FIG. 1 corresponding to the modular estimationmechanism 138 to generate the channel estimate 134 or one or moreinstances of the estimate element 136 therein. The channel estimationmodule 304 can generate the channel estimate 134 based on the weightingset 160 for characterizing the communication channel 126 for recoveringthe serving content 110. The weighting set 160 can include a referenceweight 320, a frequency weight 322, a time weight 324, afrequency-adjusted weight 326, or a combination thereof.

The reference weight 320 is one or a set of parameters for implementingthe reference processing mechanism 312. The reference weight 320 caninclude a value or a value set, such as a scalar, a calculation orprocessing result, a matrix or an array, or a combination thereofcorresponding to the reference processing mechanism 312.

The channel estimation module 304 can calculate the reference weight 320according to the reference processing mechanism 312. The channelestimation module 304 can calculate the reference weight 320 based onthe receiver signal 128, such as using the channel output portion 132,the auto-correlation result 146 of FIG. 1, the noise measure 130, or acombination thereof.

The frequency weight 322 is one or a set of parameters for implementingthe frequency-domain mechanism 314. The frequency weight 322 can includea value or a value set, such as a scalar, a calculation or processingresult, a matrix or an array, or a combination thereof corresponding tothe frequency-domain mechanism 314.

The channel estimation module 304 can calculate the frequency weight 322according to the frequency-domain mechanism 314. The channel estimationmodule 304 can calculate the frequency weight 322 based on the receiversignal 128, such as using the channel output portion 132, themulti-correlation result 144 of FIG. 1, the frequency-correlationfunction 156 of FIG. 1, the noise measure 130, or a combination thereof.

The time weight 324 is one or a set of parameters for implementing thetime-domain mechanism 316. The time weight 324 can include a value or avalue set, such as a scalar, a calculation or processing result, amatrix or an array, or a combination thereof corresponding to thetime-domain mechanism 316.

The channel estimation module 304 can calculate the time weight 324according to the time-domain mechanism 316. The channel estimationmodule 304 can calculate the time weight 324 based on the receiversignal 128, such as using the channel output portion 132, thetime-correlation function 158 of FIG. 1, the noise measure 130, or acombination thereof.

The frequency-adjusted weight 326 is one or a set of parameters forimplementing the combining mechanism 318. The frequency-adjusted weight326 can include a value or a value set, such as a scalar, a calculationor processing result, a matrix or an array, or a combination thereofcorresponding to the combining mechanism 318.

The channel estimation module 304 can calculate the frequency-adjustedweight 326 according to the combining mechanism 318. The channelestimation module 304 can calculate the frequency-adjusted weight 326based on the receiver signal 128, such as using the channel outputportion 132, the time-correlation function 158, thefrequency-correlation function 156, the auto-correlation result 146 ofFIG. 1, the multi-correlation result 144, the noise measure 130, or acombination thereof.

The channel estimation module 304 can use the modular estimationmechanism 138 to calculate the weighting set 160 corresponding todistinct process groupings or segments within the modular estimationmechanism 138. The channel estimation module 304 can utilize a referenceprocessing module 330, a frequency processing module 332, a combinationprocessing module 334, a time processing module 336, or a combinationthereof.

The channel estimation module 304 can include the reference processingmodule 330, the frequency processing module 332, the combinationprocessing module 334, the time processing module 336, or a combinationthereof each corresponding to the distinct process groupings or segmentswithin the modular estimation mechanism 138. The channel estimationmodule 304 can include the reference processing module 330, thefrequency processing module 332, the combination processing module 334,the time processing module 336, or a combination thereof with thequantity of the sub-modules corresponding to the process implementationcount 142 of FIG. 1. The channel estimation module 304 can generate thechannel estimate 134 based on the modular estimation mechanism 138including process implementation count 142 greater than one.

The channel estimation module 304 can use the reference processingmodule 330, the frequency processing module 332, the combinationprocessing module 334, the time processing module 336, or a combinationthereof to generate the channel estimate 134 based on the referenceprocessing mechanism 312, the frequency-domain mechanism 314, thecombining mechanism 318, the time-domain mechanism 316, or a combinationthereof. The channel estimation module 304 can generate the channelestimate 134 for estimating the communication channel 126 withoutcalculating and without utilizing the residual error 148 of FIG. 1 asdescribed below.

The reference processing module 330 is configured to implement thereference processing mechanism 312. The reference processing module 330can calculate, apply, or a combination thereof for the reference weight320.

The reference processing module 330 can implement the referenceprocessing mechanism 312 including a smoothing mechanism 338. Thesmoothing mechanism 338 is a method or a process for smoothing thereference portion 116. The smoothing mechanism 338 can include spectralsmoothing, shaping, filtering, interpolating, or a combination thereoffor the reference portion 116 of the receiver signal 128 or a portiontherein corresponding to the reference portion 116.

The reference processing module 330 can calculate the reference weight320 according to the reference processing mechanism 312. The referenceprocessing module 330 can calculate the reference weight 320 based onthe receiver signal 128. For example, the reference processing module330 can calculate the reference weight 320 based on the auto-correlationresult 146 of the channel output portion 132, the noise measure 130, ora combination thereof.

As a more specific example, the reference processing module 330 cancalculate the reference weight 320 based on:

W _(k) ^(RS)=(R _(pp)+σ² I)⁻¹.  Equation (6).

The reference weight 320 can be represented as ‘W_(k) ^(RS)’. Theauto-correlation result 146 for the channel output portion 132 can berepresented as ‘R_(pp) ^(’). The noise measure 130 can be represented as‘σ²I’.

The reference processing module 330 can apply the reference weight 320to the receiver signal 128 to calculate a reference processing output340. The reference processing output 340 can represent a processingresult of the reference processing mechanism 312 or the smoothingmechanism 338 therein. The reference processing output 340 can be basedon applying the reference weight 320 according to the smoothingmechanism 338 for smoothing one or more instances of the referenceportion 116.

The reference processing module 330 can calculate the referenceprocessing output 340, implement the smoothing mechanism 338, apply thereference weight 320, or a combination thereof, based on:

{circumflex over (p)} ^(T) =[{circumflex over (p)} ₁ ^(T) ,{circumflexover (p)} ₂ ^(T) , . . . ,{circumflex over (p)} _(n) ^(T)]^(T) =W _(k)^(RS) y.  Equation (7).

The reference processing output 340 can be represented as ‘{circumflexover (p)}^(T)’.

The reference processing output 340 can be the output result ofsmoothing one or more instances of the reference portion 116 in thereceiver signal 128 or segments therein corresponding to the referenceportion 116. The reference processing output 340 can further be based onapplying, such as by combining or multiplying, the reference weight 320to the receiver signal 128.

The reference processing module 330 can use the first communication unit216, the second communication unit 236, the first control unit 212, thesecond control unit 234, or a combination thereof to implement thereference processing mechanism 312. The reference processing module 330can store the reference weight 320, the reference processing output 340,or a combination thereof in the first communication unit 216, the secondcommunication unit 236, the first storage unit 214, the second storageunit 246, or a combination thereof.

The frequency processing module 332 is configured to implement thefrequency-domain mechanism 314. The frequency processing module 332 cancalculate, apply, or a combination thereof for the frequency weight 322.

The frequency processing module 332 can implement the frequency-domainmechanism 314 including a frequency-interpolation mechanism or afrequency analysis mechanism. The frequency processing module 332 cananalyze or process the frequency component or characteristic of data orsignals, such as the receiver signal 128, the reference processingoutput 340, or a combination thereof.

The frequency-domain mechanism 314 can calculate the estimate element136 corresponding to one or more instances of the resource element 114according to one or more frequency range. For example, thefrequency-domain mechanism 314 can calculate the estimate element 136for one or more instance of the resource element 114 corresponding toone or more values or instances of the carrier index 122, the frameindex 124, or a combination thereof based on the result of processing orsmoothing one or more instances of the reference portion 116. As a morespecific example, the frequency-domain mechanism 314 can calculateinstances of the estimate element 136 corresponding to the same instanceof the frame index 124 as the smoothed or processed instances of thereference portion 116 across various instances or values of the carrierindex 122.

The frequency processing module 332 can calculate the frequency weight322 according to the frequency-domain mechanism 314. The frequencyprocessing module 332 can calculate the frequency weight 322 based onthe receiver signal 128. For example, the frequency processing module332 can calculate the frequency weight 322 based on themulti-correlation result 144 of the channel output portion 132, such asaccording to:

$\begin{matrix}{W_{k,l_{i}}^{FD} = {R_{h_{k,l_{i}}p_{i}}.}} & {{Equation}\mspace{14mu} {(7).}}\end{matrix}$

The frequency weight 322 can be represented as ‘W_(k,l) _(i) ^(FD)’. Theterm ‘l_(i)’ can represent an ‘i’th instance of the symbol in thereceiver signal 128.

The multi-correlation result 144 can be calculated based on thefrequency-correlation function 156. The frequency processing module 332can calculate the multi-correlation result 144 as a frequency-onlydependent terms. The frequency processing module 332 can calculate themulti-correlation result 144 as

${‘\begin{bmatrix}R_{h_{k,l_{1}}p_{1}} & 0 & \ldots & 0 \\0 & R_{h_{k,l_{2}}p_{2}} & \ldots & \vdots \\\vdots & \vdots & \ddots & 0 \\0 & \ldots & 0 & R_{h_{k,l_{n}}p_{n}}\end{bmatrix}’}.$

The frequency processing module 332 can apply the frequency weight 322to the receiver signal 128 to calculate a frequency-domain processingoutput 342. The frequency-domain processing output 342 can represent aprocessing result of the frequency-domain mechanism 314. Thefrequency-domain processing output 342 can be based on applying thefrequency weight 322 according to the frequency-domain mechanism 314 forcharacterizing the communication channel 126 corresponding to one ormore instances of the reference portion 116 in the frequency domain 150.

The frequency processing module 332 can calculate the frequency-domainprocessing output 342, apply the frequency weight 322, or a combinationthereof, based on:

ĥ _(k,l) _(i) =W _(k,l) _(i) ^(FD) {circumflex over (p)} _(i)^(T).  Equation (8).

The frequency-domain processing output 342 can be represented as‘ĥ_(k,l) _(i) ’. The frequency processing module 332 can calculate thefrequency-domain processing output 342 subsequent to calculation for orbased on the reference processing output 340. The frequency processingmodule 332 apply the frequency weight 322 to the reference processingoutput 340 to calculate the frequency-domain processing output 342 forprocessing in the frequency domain 150.

The frequency processing module 332 can use the first communication unit216, the second communication unit 236, the first control unit 212, thesecond control unit 234, or a combination thereof to implement thefrequency-domain mechanism 314. The reference processing module 330 canstore the frequency weight 322, the frequency-domain processing output342, or a combination thereof in the first communication unit 216, thesecond communication unit 236, the first storage unit 214, the secondstorage unit 246, or a combination thereof.

The combination processing module 334 is configured to implement thecombining mechanism 318. The combination processing module 334 cancalculate, apply, or a combination thereof for the frequency-adjustedweight 326.

The combination processing module 334 can implement the combiningmechanism 318 combining the reference processing mechanism 312 and thefrequency-domain mechanism 314 into a singular process. The combinationprocessing module 334 can analyze or process the frequency component orcharacteristic of data or signals or the reference portion 116 therein.For example, the combination processing module 334 can smooth thereference portion 116 and analyze the frequency components with asingular process.

The combination processing module 334 can calculate thefrequency-adjusted weight 326 according to the combining mechanism 318.The combination processing module 334 can calculate thefrequency-adjusted weight 326 based on the receiver signal 128. Forexample, the combination processing module 334 can calculate thefrequency-adjusted weight 326 based on the auto-correlation result 146of the channel output portion 132, the noise measure 130, themulti-correlation result 144, the frequency-correlation function 156, atime-correlation set 344, a normalization adjustor 346, or a combinationthereof.

The time-correlation set 344 is a set of values or parameters resultingfrom the time-correlation function 158 for the receiver signal 128. Thetime-correlation set 344 can be represented as ‘R_(t)’. Thetime-correlation set 344 can further include a n-by-n matrix with aresult of comparing two symbols at ‘i’ and ‘j’ with the time-correlationfunction 158, according to ‘r_(t)(l_(i)−l_(j))’, as the (i,j)-th entry.

The normalization adjustor 346 is a value, a parameter, a set thereof,or a combination thereof for adjusting the calculation for thefrequency-adjusted weight 326. The normalization adjustor 346 can berepresented as ‘(R_(t)+δ²I)’. The normalization adjustor 346 can bebased on the time-correlation set 344.

The normalization adjustor 346 can include an arbitrary value or a setof values predetermined by the computing system 100, the first device102, the second device 106, or a combination thereof. The arbitraryvalue or the set of values can be employed for controlling matrixmanipulation and avoid ill-conditioned matrix inversion. The arbitraryvalue or the set of values can be represented as ‘δ’.

As a more specific example, the combination processing module 334 cancalculate the frequency-adjusted weight 326 based on:

$\begin{matrix}{W_{k}^{FD} = {{{\left( {R_{t} + {\delta^{2}I}} \right)\begin{bmatrix}R_{h_{k,l_{1}}p_{1}} & 0 & \ldots & 0 \\0 & R_{h_{k,l_{2}}p_{2}} & \ldots & \vdots \\\vdots & \vdots & \ddots & 0 \\0 & \ldots & 0 & R_{h_{k,l_{n}}p_{n}}\end{bmatrix}}\left( {R_{pp} + {\sigma^{2}I}} \right)^{- 1}}..}} & {{Equation}\mspace{14mu} (9)}\end{matrix}$

The frequency-adjusted weight 326 can be represented as ‘W_(k) ^(FD)’.

The combination processing module 334 can apply the frequency-adjustedweight 326 to the receiver signal 128 to calculate the frequency-domainprocessing output 342. The combination processing module 334 cancalculate the frequency-adjusted weight 326 based on applying thefrequency-adjusted weight 326 to the receiver signal 128 for smoothingone or more instances of the reference portion 116 and processing in afrequency domain 150.

The frequency-domain processing output 342 from the combinationprocessing module 334 can represent a processing result of thefrequency-domain mechanism 314. The frequency-domain processing output342 for the combination processing module 334 can be based on applyingthe frequency-adjusted weight 326 according to the combining mechanism318 for combining the reference processing mechanism 312 and thefrequency-domain mechanism 314 into the process implementation count 142of one.

The combination processing module 334 can calculate the frequency-domainprocessing output 342 corresponding to the combining mechanism 318 basedon:

[ĥ _(k,l) ₁ ,ĥ _(k,l) ₂ , . . . ,ĥ _(k,l) _(n) ]^(T)′.  Equation (10).

The frequency-domain processing output 342 corresponding to thecombining mechanism 318 can be represented as ‘[ĥ_(k,l) ₁ ,ĥ_(k,l) ₂ , .. . ,ĥ_(k,l) _(n) ]^(T)’.

The combination processing module 334 can use the first communicationunit 216, the second communication unit 236, the first control unit 212,the second control unit 234, or a combination thereof to implement thecombining mechanism 318. The combination processing module 334 can storethe frequency-adjusted weight 326, the frequency-domain processingoutput 342, the normalization adjustor 346, or a combination thereof inthe first communication unit 216, the second communication unit 236, thefirst storage unit 214, the second storage unit 246, or a combinationthereof.

The channel estimation module 304 can calculate the frequency-domainprocessing output 342 using the reference processing module 330 firstand then the frequency processing module 332. The channel estimationmodule 304 can alternatively calculate the frequency-domain processingoutput 342 using the combination processing module 334.

The time processing module 336 is configured to implement thetime-domain mechanism 316. The time processing module 336 can calculate,apply, or a combination thereof for the time weight 324.

The time processing module 336 can implement the time-domain mechanism316 including a time-domain interpolation mechanism or a time-domainanalysis mechanism. The time processing module 336 can analyze orprocess the time component or characteristic of data or signals, such asthe receiver signal 128, the frequency-domain processing output 342, ora combination thereof.

The time processing module 336 can calculate the time weight 324according to the time-domain mechanism 316. The time processing module336 can calculate the time weight 324 based on the receiver signal 128.For example, the time processing module 336 can calculate the timeweight 324 based on the time-correlation function 158, the normalizationadjustor 346, or a combination thereof, such as according to:

W _(l) ^(TD) =[r _(t)(l−l ₁) . . . r _(t)(l−l _(n))].  Equation (11).

The time weight 324 can be represented as ‘W_(l) ^(TD)’.

The time processing module 336 can calculate the time weight 324differently or adjust for the frequency-domain processing output 342based on the combining mechanism 318 instead of the reference processingmechanism 312 and the frequency-domain mechanism 314. The timeprocessing module 336 can calculate the time weight 324 differently oradjust the time weight 324 based on the normalization adjustor 346. Forexample, the time processing module 336 can calculate the time weight324 according to:

W _(l) ^(TD) =[r _(t)(l−l ₁) . . . r _(t)(l−l _(n))](R _(t)+δ¹I)⁻¹.  Equation (12).

The time processing module 336 can apply the time weight 324 accordingto the time-domain mechanism 316 for interpolating the communicationchannel 126 between one or more instances of the reference portion 116.The time processing module 336 can process the data or the informationexisting in the time domain 152, perform the processing in the timedomain 152, or a combination thereof. The time processing module 336 canfurther interpolate the data corresponding to the resource element 114between instances of the reference portion 116 that have been smoothedand processed in the frequency domain 150.

The time processing module 336 can apply the time weight 324 to processfor the time domain 152, interpolate, or a combination thereof. The timeprocessing module 336 can generate the channel estimate 134 or theestimate element 136 therein based on applying the time weight 324 tothe frequency-domain processing output 342. The time processing module336 can apply the time weight 324 based on:

ĥ _(k,l) =W _(l) ^(TD) [ĥ _(k,l) ₁ ,ĥ _(k,l) ₂ , . . . ,ĥ _(k,l) _(n)]^(T).  Equation (13).

The channel estimate 134 or the estimate element 136 therein can berepresented as ‘ĥ_(k,l)’.

The time-domain mechanism 316 can calculate the estimate element 136corresponding to one or more instances of the resource element 114according to one or more time slot. For example, the time-domainmechanism 316 can calculate the estimate element 136 for one or moreinstance of the resource element 114 corresponding to one or more valuesor instances of the carrier index 122, the frame index 124, or acombination thereof based on the result of processing in the frequencydomain 150. As a more specific example, the time-domain mechanism 316can calculate instances of the estimate element 136 corresponding to aparticular instance of the frame index 124 different from the referenceportion 116.

It has been discovered that the channel estimate 134 or the estimateelement 136 therein based on the reference weight 320, the frequencyweight 322, and the time weight 324 corresponding to the referenceprocessing mechanism 312, the frequency-domain mechanism 314, and thetime-domain mechanism 316 provide reduction in computational complexityand improved accuracy in estimating the communication channel 126. Themodular estimation mechanism 138 utilizing 3 different steps cantrade-off slight expansion in non-dominant process for fullymanipulating the pilot symbols to reduce the complexity in the dominantprocess overall.

It has further been discovered that the channel estimate 134 or theestimate element 136 therein based on the frequency-adjusted weight 326and the time weight 324 corresponding to the combining mechanism 318 andthe time-domain mechanism 316 provide reduction in computationalcomplexity and improved accuracy in estimating the communication channel126. The modular estimation mechanism 138 utilizing 2 different stepscan trade-off slight expansion in non-dominant process for fullymanipulating the pilot symbols to reduce the complexity in the dominantprocess overall.

It has further been discovered that the channel estimate 134 or theestimate element 136 therein generated without the residual error 148provide increased accuracy in estimating the communication channel 126while reducing computational complexity. The modular estimationmechanism 138 as described above can eliminate calculation of additionalparameter of the residual error 148. The modular estimation mechanism138 can utilize the noise measure 130 without further evaluating anerror introduced within the processing to characterize the communicationchannel 126.

It has further been discovered that the channel estimate 134 or theestimate element 136 therein generated with the modular estimationmechanism 138 instead of the naïve-comprehensive mechanism 140 providereduction in number of computations or iterations. The modularestimation mechanism 138 using the staged calculation can reduce theoverall number of multiplications required for generating the channelestimate 134 or the estimate element 136 therein compared to thenaïve-comprehensive mechanism 140 calculating 2 dimensional MMSE channelestimate using a comprehensive approach according to

${‘{\underset{\underset{({2D\mspace{14mu} {MMSE}\mspace{14mu} {weight}\mspace{14mu} {matrix}})}{}}{{R_{h_{k,l}p}\left( {R_{pp} + {\sigma^{2}I}} \right)}^{- 1}}\mspace{11mu} y}’}.$

The staged calculations can reduce the compounded effect frommanipulating large sets of data for complex computations by simplifyingthe computation, reducing the size of the data, or a combinationthereof.

It has further been discovered that the channel estimate 134 or theestimate element 136 therein generated based on the normalizationadjustor 346 provides increased accuracy in estimating the communicationchannel 126 while reducing computational complexity. The normalizationadjustor 346 can simplify the values for computation and control theprocessing appropriately at each step or stage in generating the channelestimate 134 or the estimate element 136.

After estimating the communication channel 126, the control flow can bepassed from the channel estimation module 304 to the message processingmodule 306. The control flow can pass similarly as described abovebetween the receiver module 302 and the channel estimation module 304but using processing results of the channel estimation module 304, suchas the channel estimate 134.

The message processing module 306 is configured to process for theserving content 110. The message processing module 306 can detect,decode, or a combination thereof for the receiver signal 128 torecognize, recover, or estimate the serving signal 108, the servingcontent 110, or a combination thereof from the receiver signal 128 basedon the channel estimate 134.

For example, the message processing module 306 can calculate likelihoodvalues, such as logarithmic likelihood ratio (LLR), for a portion of thereceiver signal 128 corresponding to one or more of the symbols, bits,or a combination thereof transmitted for the serving signal 108 based onthe channel estimate 134. Also for example, the message processingmodule 306 can calculate LLR for bits or code word corresponding to theserving signal 108 or the serving content 110 intended for communicationbased on the channel estimate 134. Also for example, the messageprocessing module 306 can implement error check or content verification,error correction, for the information processed from the receiver signal128.

The message processing module 306 can use iterative configurations, suchas for iterative detection-decoding configuration or successivecancelling configuration to process for or recover the serving content110. The message processing module 306 can further useinterference-aware processing mechanism to process for or recover theserving content 110.

The message processing module 306 can use the serving content 110recovered or estimated from the receiver signal 128 based on the channelestimate 134. The computing system 100 can communicate the recovered orestimated instance of the serving content 110 to the user, to anotherdevice, or a combination thereof.

For example, the first device 102 can display, audibly recreate, causehaptic feedback, or a combination thereof according to the servingcontent 110 for communicating to the user. Also for example, the firstdevice 102 can further process, transmit, relay, or a combinationthereof to communicate with another device. Also for example, the firstdevice 102 can implement the serving content 110, such as forconfiguration, data storage, instruction execution, or a combinationthereof.

The message processing module 306 can use the first communication unit216, the second communication unit 236, the first control unit 212, thesecond control unit 234, or a combination thereof to process for theserving content 110. The message processing module 306 can store theprocessing results, such as the serving content 110, in the firstcommunication unit 216, the second communication unit 236, the firststorage unit 214, the second storage unit 246, or a combination thereof.

Referring now to FIG. 4, therein is shown a flow chart 400 of a methodof operation of a computing system in a further embodiment. The method400 includes: receiving receiver signal for communicating servingcontent through a communication channel in a block 402; calculating aweighting set corresponding to a modular estimation mechanism in a block404; and generating a channel estimate set with a communication unitbased on the weighting set for characterizing the communication channelfor recovering the serving content in a block 406.

The modules described in this application can be hardware implementationor hardware accelerators, including passive circuitry, active circuitry,or both, in the first communication unit 216 of FIG. 2, the secondcommunication unit 236 of FIG. 2, the first control unit 212 of FIG. 2,the second control unit 238 of FIG. 2, or a combination thereof. Themodules can also be hardware implementation or hardware accelerators,including passive circuitry, active circuitry, or both, within the firstdevice 102 of FIG. 1, the second device 106 of FIG. 1, or a combinationthereof but outside of the first communication unit 216, the secondcommunication unit 236, the first control unit 212, the second controlunit 234, or a combination thereof.

The computing system 100 of FIG. 1 has been described with modulefunctions or order as an example. The computing system 100 can partitionthe modules differently or order the modules differently. For example,the channel estimation module 304 of FIG. 3 and the receiver module 302of FIG. 3 can be combined. Also for example, the calculation for theweighting set 160 of FIG. 1 in the reference processing module 330 ofFIG. 3, the frequency processing module 332 of FIG. 3, the combinationprocessing module 334 of FIG. 3, the time processing module 336 of FIG.3, or a combination thereof can be separated into one or a group ofmodules.

For illustrative purposes, the various modules have been described asbeing specific to the first device 102, the second device 106, or acombination thereof. However, it is understood that the modules can bedistributed differently. For example, the various modules can beimplemented in a different device, or the functionalities of the modulescan be distributed across multiple devices. Also as an example, thevarious modules can be stored in a non-transitory memory medium.

As a more specific example, one or more modules described above can bestored in the non-transitory memory medium for distribution to adifferent system, a different device, a different user, or a combinationthereof, for manufacturing, or a combination thereof. Also as a morespecific example, the modules described above can be implemented orstored using a single hardware unit, such as a chip or a processor, oracross multiple hardware units.

The modules described in this application can be stored in thenon-transitory computer readable medium. The first communication unit216, the second communication unit 236, the first control unit 212, thesecond control unit 234, or a combination thereof can represent thenon-transitory computer readable medium. The first communication unit216, the second communication unit 236, the first control unit 212, thesecond control unit 234, or a combination thereof, or a portion thereincan be removable from the first device 102, the second device 106, or acombination thereof. Examples of the non-transitory computer readablemedium can be a non-volatile memory card or stick, an external hard diskdrive, a tape cassette, or an optical disk.

The physical transformation of the channel estimate 134 of FIG. 1results in the movement in the physical world, such as content displayedor recreated for the user on the first device 102 from processing theserving content 110 of FIG. 1 therein. The content reproduced on thefirst device 102, such as navigation information or voice signal of acaller, can influence the user's movement, such as following thenavigation information or replying back to the caller. Movement in thephysical world results in changes to the geographic location of thefirst device 102 and correspondingly to the communication channel 126 ofFIG. 1, which can be fed back into the computing system 100 andinfluence the channel estimate 134.

The resulting method, process, apparatus, device, product, and/or systemis straightforward, cost-effective, uncomplicated, highly versatile,accurate, sensitive, and effective, and can be implemented by adaptingknown components for ready, efficient, and economical manufacturing,application, and utilization. Another aspect of an embodiment describedherein is that it valuably supports and services the historical trend ofreducing costs, simplifying systems, and increasing performance.

These and other valuable aspects of an embodiment consequently furtherthe state of the technology to at least the next level.

While the embodiments have been described in conjunction with a specificbest mode, it is to be understood that many alternatives, modifications,and variations will be apparent to those skilled in the art in light ofthe aforegoing description. Accordingly, it is intended to embrace allsuch alternatives, modifications, and variations that fall within thescope of the included claims. All matters set forth herein or shown inthe accompanying drawings are to be interpreted in an illustrative andnon-limiting sense.

1. A computing system comprising: an inter-device interface configuredto receive receiver signal for communicating serving content through acommunication channel, the receiver signal including reference portions;a communication unit, coupled to the inter-device interface, configuredto: calculate a weighting set corresponding to a modular estimationmechanism including a smoothing mechanism for smoothing the referenceportions, the weighting set including a reference weight for applicationaccording to the smoothing mechanism, and generate a channel estimatebased on the weighting set for characterizing the communication channelfor recovering the serving content.
 2. The system as claimed in claim 1wherein the communication unit is configured to: calculate the weightingset according to the modular estimation mechanism including a referenceprocessing mechanism, a frequency-domain mechanism, and a time-domainmechanism; and generate the channel estimate based on the referenceprocessing mechanism, the frequency-domain mechanism, and thetime-domain mechanism.
 3. The system as claimed in claim 1 wherein thecommunication unit is configured to: calculate the weighting setaccording to the modular estimation mechanism including a combiningmechanism and a time-domain mechanism; and generate the channel estimatebased on the combining mechanism and the time-domain mechanism.
 4. Thesystem as claimed in claim 1 wherein the communication unit isconfigured to generate the channel estimate for estimating thecommunication channel without using residual error.
 5. The system asclaimed in claim 1 wherein the communication unit is configured togenerate the channel estimate based on the modular estimation mechanismincluding process implementation count greater than one.
 6. The systemas claimed in claim 1 wherein the communication unit is configured togenerate the channel estimate based on the modular estimation mechanismfor replacing a naïve-comprehensive mechanism.
 7. The system as claimedin claim 6 wherein: the inter-device interface is configured to receivethe receiver signal including reference portions; the communication unitis configured to: calculate the weighting set including a frequencyweight, and a time weight according to the modular estimation mechanismincluding a frequency-domain mechanism, and a time-domain mechanism;generate the channel estimate based on: applying the reference weightaccording to the smoothing mechanism for smoothing the referenceportions, applying the frequency weight according to thefrequency-domain mechanism for characterizing the communication channelcorresponding to the reference portions, and applying the time weightaccording to the time-domain mechanism for interpolating thecommunication channel between the reference portions.
 8. The system asclaimed in claim 6 wherein the communication unit is configured to:calculate the weighting set including a frequency-adjusted weightcalculated based on a normalization adjustor according to the modularestimation mechanism including a combining mechanism; generate thechannel estimate based on applying the frequency-adjusted weightaccording to the combining mechanism for combining a referenceprocessing mechanism and a frequency-domain mechanism into a processimplementation count of one.
 9. The system as claimed in claim 6 whereinthe communication unit is configured to: calculate a referenceprocessing output based on applying a reference weight to the receiversignal; calculate a frequency-domain processing output based on applyinga frequency weight to the reference processing output for processing ina frequency domain; and generate the channel estimate based on applyinga time weight to the frequency-domain processing output for processingin a time domain.
 10. The system as claimed in claim 6 wherein: theinter-device interface is configured to receive the receiver signalincluding reference portions; the communication unit is configured to:calculate a frequency-domain processing output based on applying afrequency-adjusted weight to the receiver signal for smoothing thereference portions and processing in a frequency domain; and generatethe channel estimate based on applying a time weight to thefrequency-domain processing output for processing in a time domain. 11.A method of operation of a computing system comprising: receivingreceiver signal for communicating serving content through acommunication channel, the receiver signal including reference portions;calculating a weighting set corresponding to a modular estimationmechanism including a smoothing mechanism for smoothing the referenceportions, the weighting set including a reference weight for applicationaccording to the smoothing mechanism; and generating a channel estimatewith a communication unit based on the weighting set for characterizingthe communication channel for recovering the serving content.
 12. Themethod as claimed in claim 11 wherein: calculating the weighting setincludes calculating the weighting set according to the modularestimation mechanism including a reference processing mechanism, afrequency-domain mechanism, and a time-domain mechanism; and generatingthe channel estimate includes generating the channel estimate based onthe reference processing mechanism, the frequency-domain mechanism, andthe time-domain mechanism.
 13. The method as claimed in claim 11wherein: calculating the weighting set includes calculating theweighting set according to the modular estimation mechanism including acombining mechanism and a time-domain mechanism; and generating thechannel estimate includes generating the channel estimate based on thecombining mechanism and the time-domain mechanism.
 14. The method asclaimed in claim 11 wherein generating the channel estimate includesgenerating the channel estimate for estimating the communication channelwithout using residual error.
 15. The method as claimed in claim 11wherein generating the channel estimate includes generating the channelestimate based on the modular estimation mechanism including processimplementation count greater than one.
 16. A non-transitory computerreadable medium including instructions that when executed by a computingsystem performs a method comprising: receiving receiver signal forcommunicating serving content through a communication channel, thereceiver signal including reference portions; calculating a weightingset corresponding to a modular estimation mechanism including asmoothing mechanism for smoothing the reference portions, the weightingset including a reference weight for application according to thesmoothing mechanism; and generating a channel estimate with acommunication unit based on the weighting set for characterizing thecommunication channel for recovering the serving content.
 17. Thenon-transitory computer readable medium as claimed in claim 16 wherein:calculating the weighting set includes calculating the weighting setaccording to the modular estimation mechanism including a referenceprocessing mechanism, a frequency-domain mechanism, and a time-domainmechanism; and generating the channel estimate includes generating thechannel estimate based on the reference processing mechanism, thefrequency-domain mechanism, and the time-domain mechanism.
 18. Thenon-transitory computer readable medium as claimed in claim 16 wherein:calculating the weighting set includes calculating the weighting setaccording to the modular estimation mechanism including a combiningmechanism and a time-domain mechanism; and generating the channelestimate includes generating the channel estimate based on the combiningmechanism and the time-domain mechanism.
 19. The non-transitory computerreadable medium as claimed in claim 16 wherein generating the channelestimate includes generating the channel estimate for estimating thecommunication channel without using residual error.
 20. Thenon-transitory computer readable medium as claimed in claim 16 whereingenerating the channel estimate includes generating the channel estimatebased on the modular estimation mechanism including processimplementation count greater than one.